We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks at nonzero chemical potential. After integrating out the gauge fields at infinite coupling, the partition function can be written as a full contraction of a tensor network consisting of coupled local numeric and Grassmann tensors. To evaluate the partition function and to compute observables, we develop a Grassmann higher-order tensor renormalization group method, specifically tailored for this model. During the coarsening procedure, the blocking of adjacent Grassmann tensors is performed analytically, and the total number of Grassmann variables in the tensor network is reduced by a factor of two at each coarsening step. The coarse-site numeri...
We show how to apply renormalization group algorithms incorporating entanglement filtering methods a...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
Recently, the tensor network description with bond weights on its edges has been proposed as a novel...
We discuss the successes and limitations of statistical sampling for a sequence of models studied in...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We formulate the path integral of two- and three-flavor Wilson fermion in two dimensions as a multil...
We present a new tensor network algorithm for calculating the partition function of interacting quan...
We make a detailed analysis of the spontaneous Z2-symmetry breaking in the two dimensional real ϕ4 t...
We show how to apply renormalization group algorithms incorporating entanglement filtering methods a...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
We present a tensor-network approach for two-dimensional strong-coupling QCD with staggered quarks a...
Recently, the tensor network description with bond weights on its edges has been proposed as a novel...
We discuss the successes and limitations of statistical sampling for a sequence of models studied in...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We calculate thermodynamic potentials and their derivatives for the three-dimensional O(2) model usi...
We formulate the path integral of two- and three-flavor Wilson fermion in two dimensions as a multil...
We present a new tensor network algorithm for calculating the partition function of interacting quan...
We make a detailed analysis of the spontaneous Z2-symmetry breaking in the two dimensional real ϕ4 t...
We show how to apply renormalization group algorithms incorporating entanglement filtering methods a...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...
We introduce a coarse-graining transformation for tensor networks that can be applied to study both ...